Abstract
Background. Far-Field R-Wave (FFRW) oversensing and P wave blanking are the major causes of inaccurate atrial signal classification in current pacemaker (PM) devices leading to inaccurate stored diagnostic information and to inadequate PM reactions like mode-switching or preventive pacing. The prospective and multi-center MARS (Morphology of Atrial Signals) study therefore investigated during daily life the capabilities of Digital Signal Processing (DSP) in an implanted dual chamber PM to improve P-wave classification accuracy. Methods . 55 patients with an implanted dual chamber PM (Vitatron T- or C-series) were included: During 24 hours with daily life activity and a stress test, a Holter ECG collected surface ECG, PM markers and all atrial EGM’s. The DSP algorithm analysed atrial events sensed nearby a ventricular event using the minimum and the maximum amplitude of the digitalized and filtered signal and the maximum and minimum amplitude of the slope signal. After comparing to the characteristics of a normal P wave, each of these atrial signals were then classified as a true atrial signal or FFRW. DSP classification results were then compared to the conventional PM signal classification by three independent reviewers. Results . Classification accuracy for the traditional PM functionality after optimizing blanking and sensitivity settings was 97.1% (19.5–100%) as compared to 99.4% (76.9–100%) using the DSP algorithm (p<0.001). Conclusion . The DSP algorithm significantly improved the classification accuracy of sensed atrial events as an important prerequisite for a correct diagnostic and therapeutic PM function. The herewith presented approach of analysing atrial signals by form and timing may allow to reduce or even eliminate atrial blanking periods thus leading to larger PM sensing windows to prevent from atrial tachyarrhythmia undersensing without an increase in FFRW sensing.
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